Pulse oximetry is at present the standard of care for continuous monitoring of arterial oxygen saturation (SpO2). Pulse oximeters provide instantaneous in-vivo measurements of arterial oxygenation, and thereby an early warning of arterial hypoxemia, for example.
A pulse oximeter comprises a computerized measuring unit and a probe attached to the patient, typically to a finger or ear lobe. The probe includes a light source for sending an optical signal through the tissue and a photo detector for receiving the signal after transmission through the tissue. On the basis of the transmitted and received signals, light absorption by the tissue can be determined. During each cardiac cycle, light absorption by the tissue varies cyclically. During the diastolic phase, absorption is caused by venous blood, tissue, bone, and pigments, whereas during the systolic phase there is an increase in absorption, which is caused by the influx of arterial blood into the tissue. Pulse oximeters focus the measurement on this arterial blood portion by determining the difference between the peak absorption during the systolic phase and the constant absorption during the diastolic phase. Pulse oximetry is thus based on the assumption that the pulsatile component of the absorption is due to arterial blood only.
Light transmission through an ideal absorbing sample is determined by the known Lambert-Beer equation as follows:Iout=Iine−εDC,  (1)where Iin is the light intensity entering the sample, Iout is the light intensity received from the sample, D is the path length through the sample, ε is the extinction coefficient of the analyte in the sample at a specific wavelength, and C is the concentration of the analyte. When Iin, D, and ε are known, and Iout is measured, the concentration C can be calculated.
In pulse oximetry, in order to distinguish between two species of hemoglobin, oxyhemoglobin (HbO2), and deoxyhemoglobin (RHb), absorption must be measured at two different wavelengths, i.e. the probe includes two different light emitting diodes (LEDs). The wavelength values widely used are 660 nm (red) and 940 nm (infrared), since the said two species of hemoglobin have substantially different absorption values at these wavelengths. Each LED is illuminated in turn at a frequency which is typically several hundred Hz.
The accuracy of a pulse oximeter is affected by several factors. This is discussed briefly in the following.
Firstly, the dyshemoglobins which do not participate in oxygen transport, i.e. methemoglobin (MetHb) and carboxyhemoglobin (COHb), absorb light at the wavelengths used in the measurement. Pulse oximeters are set up to measure oxygen saturation on the assumption that the patient's blood composition is the same as that of a healthy, non-smoking individual. Therefore, if these species of hemoglobin are present in higher concentrations than normal, a pulse oximeter may display erroneous data.
Secondly, intravenous dyes used for diagnostic purposes may cause considerable deviation in pulse oximeter readings. However, the effect of these dyes is short-lived since the liver purifies blood efficiently.
Thirdly, coatings like nail polish may in practice impair the accuracy of a pulse oximeter, even though the absorption caused by them is constant, not pulsatile, and thus in theory it should not have an effect on the accuracy.
Fourthly, the optical signal may be degraded by both noise and motion artifacts. One source of noise is the ambient light received by the photodetector. Many solutions have been devised with the aim of minimizing or eliminating the effect of the movement of the patient on the signal, and the ability of a pulse oximeter to function correctly in the presence of patient motion depends on the design of the pulse oximeter. One way of canceling out the motion artefact is to use an extra wavelength for this purpose.
A further factor affecting the accuracy of a pulse oximeter is the method used to calibrate the pulse oximeter. Usually the calibration is based on extensive empirical studies in which an average calibration curve is determined based on a high number of persons. By means of this calibration curve, which relates the oxygen saturation of blood to pulse oximeter signals, the average difference between the theory and practice (i.e. in-vivo measurements) is taken into account. The calibration curve typically maps the measured in-vivo signal to a corresponding SpO2 value.
Pulse oximeters, however, can also utilize the Lambert-Beer model for calculating the concentrations of the different Hb species. In this method of calibration, the measurement signals must first be transformed into signals applicable to the Lambert-Beer model for calculation. This transformation constitutes the calibration of the pulse oximeter, since it is the step which adapts the in-vivo signals to the Lambert-Beer theory, according to which the pulse oximeter is designed to operate. Thus, the calibration curves can also be in the form of transformations used to adapt the actual in-vivo measurements to the Lambert-Beer model.
Transformations are discussed for example in U.S. Pat. No. 6,104,938, which discloses a calibration method based on the absorption properties of each hemoglobin component, i.e. on the extinction coefficients of blood. In this method, the effective extinction coefficients are determined for each light signal via a mathematical transformation from the extinction coefficients according to the Lambert-Beer theory.
Below, the solution according to the invention is discussed with reference to a pulse oximeter utilizing the above-mentioned transformations and four different wavelengths. As mentioned above, U.S. Pat. No. 6,104,938 discloses a pulse oximeter utilizing the transformations.
FIG. 1 is a block diagram of a pulse oximeter utilizing four different wavelengths. Light from four different LEDs 10a, 10b, 10c, and 10d, each operating at a respective wavelength, passes into patient tissue, such as a finger 11. The light propagated through or reflected from the tissue is received by a photodetector 12, which converts the optical signal received into an electrical signal and feeds it to an input amplifier 13. The amplified signal is then supplied to a control unit 14, which carries out calculation of the amount of the Hb-derivatives in the blood. The control unit further controls the LED drive 15 to alternately activate the LEDs. As mentioned above, each LED is typically illuminated several hundred times per second.
When each LED is illuminated at such a high rate as compared to the pulse rate of the patient, the control unit obtains a high number of samples at each wavelength for each cardiac cycle of the patient. The value of these samples (i.e. the amplitude of the received signal) varies according to the cardiac cycle of the patient, the variation being caused by the arterial blood, as mentioned above. The control unit 14 therefore utilizes four measurement signals, as shown in FIG. 2, each being received at one of the wavelengths.
In order for variations in extrinsic factors, such as the brightness of the LEDs, sensitivity of the detector, or thickness of the finger, to have no effect on the measurement, each signal received is normalized by extracting the AC component oscillating at the cardiac rhythm of the patient, and then dividing the AC component by the DC component of the light transmission or reflection. The signal thus obtained is independent of the above-mentioned extrinsic factors. Thus in this case the control unit utilizes four normalized signals, which are in the following denoted with
            dA      i        =                  A        ⁢                                  ⁢                  C          i                            D        ⁢                                  ⁢                  C          i                      ,where i is the wavelength in question (in this basic embodiment of the multi-wavelength pulse oximeter i=1, 2, 3, 4), ACi is the AC component at wavelength i, and DCi is the DC component at wavelength i. The signals dAi are also referred to below as modulation signals. The modulation signals thus indicate how absorption is affected by the arterial blood of the patient.
The above-described measurement arrangement corresponds to a conventional four-wavelength pulse oximeter. The operation of the pulse oximeter is discussed in more detail below.
The theory of pulse oximetry is generally presented as being based on the Lambert-Beer Law. According to this theory, light transmission through the tissue at each wavelength is exponentially dependent on the absorbance of the tissue (Eq. 1). This theory is generally accepted and established as a good model for pulse oximetry.
Next to be discussed is the theory and formalism on which the method of the invention is based.
According to the Lambert-Beer theory and for a system of two analytes, the signals described above can be presented as follows:dA1=dA×(ε1HbO2×HbO2+ε1RHb×RHb)dA2=dA×(ε2HbO2×HbO2+ε2RHb×RHb)dA3=dA×(ε3HbO2×HbO2+ε3RHb×RHb)dA4=dA×(ε4HbO2×HbO2+ε4RHb×RHb)RHb=1−HbO2 
where dA is a common factor which depends on the absolute values, i.e. inter alia on the total amount of hemoglobin, εiHbO2 is the extinction coefficient of oxyhemoglobin at wavelength i (i=1−4), εiRHb is the extinction coefficient of deoxyhemoglobin at wavelength i, HbO2 is the concentration fraction of oxyhemoglobin, and RHb is the concentration fraction of deoxyhemoglobin.
Using a matrix notation, the above dependencies can be expressed for a system of n wavelengths and n analytes as follows:
                                          (                                                                                dA                    1                                                                                                                    dA                    2                                                                                                ⋯                                                                                                  dA                    n                                                                        )                    =                      C            *                                          (                                                                                                                              ɛ                          11                                                ⁢                                                                                                  ⁢                        …                        ⁢                                                                                                  ⁢                                                  ɛ                                                      1                            ⁢                            n                                                                                                                                                                                                                                                        ɛ                            ⁢                                                                                                                                          21                                                ⁢                                                                                                  ⁢                        …                        ⁢                                                                                                  ⁢                                                  ɛ                                                      2                            ⁢                            n                                                                                                                                                                          ⋯                                                                                                                                                    ɛ                                                      n                            ⁢                                                                                                                  ⁢                            1                                                                          ⁢                                                                                                  ⁢                        …                        ⁢                                                                                                  ⁢                                                  ɛ                          nn                                                                                                                    )                            ·                              (                                                                                                    HbX                        1                                                                                                                                                HbX                        2                                                                                                                        ⋯                                                                                                                          HbX                        n                                                                                            )                                                    ,                            (        2        )            
where dAi is the differential change in absorption (i.e. the modulation signal) at wavelength λi, εij is the extinction coefficient of the hemoglobin derivative HbXj at wavelength λi, and the constant C accounts for the change of units to fractional percentages of the concentrations of the analytes HbXj.
FIG. 3 shows the extinction coefficients (εHbO2 and εRHb) of oxyhemoglobin (HbO2) and deoxyhemoglobin (RHb) as a function of the wavelength. Point P shown in the figure is the isobestic point of oxyhemoglobin (HbO2) and deoxyhemoglobin (RHb). The point has the special property that the modulation signal at the wavelength in question does not depend on the respective proportions (relative concentrations) of the hemoglobin species. Thus at the wavelength of point P the effect of the relative concentrations of oxyhemoglobin and deoxyhemoglobin on the result of the measurement is nil. It should be noted, however, that the modulation signal is independent of the relative concentrations only, not of the absolute concentrations. Thus, the absolute amount of the hemoglobin species has an effect on the result of the measurement.
As is known, there is a difference between the Lambert-Beer theory and the practical measurements. The difference is due to the fact that the Lambert-Beer theory does not take into account the scattering and non-homogeneity of the tissue, whereas the actual extinction coefficients are also dependent on the scattering of light caused by the tissue and blood, and on the combined effect of absorption and scattering. The larger the proportion of the attenuation caused by absorption and scattering, the larger is the correction needed between the actual and the theoretical (non-scatter) domains. This correction between these two domains can be represented by the transformation curves discussed above, by means of which the actual in-vivo measurements are mapped to the Lambert-Beer model.
The transformation can be expressed, for example, as follows:
                                          N            kl                          L              -              B                                =                                                                      g                  kl                                      -                    1                                                  ⁡                                  (                                      N                    kl                                                                  i                        ⁢                                                                                                  ⁢                        n                                            -                      vivo                                                        )                                            ⁢                                                          ⁢              where              ⁢                                                          ⁢                              N                kl                                      =                                          ⅆ                                  A                  k                                                            ⅆ                                  A                  l                                                                    ,                            (        3        )            is the modulation ratio (the superscript indicating the domain) and the subscripts k and l indicating the wavelengths in question), and g is the transformation, for instance in the form of a polynomial function, transforming the L-B N-values to the corresponding N-values in the in-vivo domain. The g−1 in Eq. 3 is the inverse transformation, i.e. the inverse function, for transforming the measured in-vivo values to the ideal, non-scatter, values in the L-B domain
FIGS. 4a to 4f illustrate the average transformation curves measured for a pulse oximeter, where the two wavelengths for measuring the two species of hemoglobin are 660 nm and 900 nm and the third wavelength is either 725 nm or 805 nm. FIGS. 4a to 4c illustrate the transformation curves for a pulse oximeter with the third wavelength being 725 nm, and FIGS. 4d to 4f illustrate the transformation curves for a pulse oximeter with the third wavelength being 805 nm. Each curve shows the Lambert-Beer Nk,l as a function of the in-vivo Nkl at wavelengths k and l.
FIG. 5 is a flow diagram describing the general measurement principle described in U.S. Pat. No. 6,104,938. In this method, the above-mentioned Nklin-vivo values are first determined from the dAi values measured (step 51). The average transformations gkl are then used to convert the measured in-vivo values to values NklL-B, which can be used in the ideal Lambert-Beer model (step 52). Other input values needed for the Lambert-Beer model are also determined (step 53). In practice these input values are the ideal (nominal) extinction coefficients of the analytes to be measured, the extinction coefficients being given for the center wavelengths used in the measurement. The converted transformation values and the nominal input values (i.e. nominal extinction coefficients) are then used according to the Lambert-Beer model to calculate the concentrations of the desired analytes (step 54). Thus in this approach the in-vivo values Nklin-vivo measured from the tissue are converted to the ideal in-vitro (cuvette) environment, where the ideal oximetry model (i.e. the Lambert-Beer model) is applied to yield the desired concentrations.
In the standard two wavelength pulse oximetry the prior art technique is to map the modulation ratio Nklin-vivo directly to the SpO2 percentage measured. In this simple case the transformation is not necessary, though the transformation technique together with the solution in the Lambert-Beer domain can be utilized as well.
There are two basic ways to determine the average transformation, a theoretical approach and an empirical approach. In the empirical approach the measurements are made in the tissue by taking blood samples and measuring the actual proportions of the hemoglobin species and then determining the value of NklL-B on the basis of the measured proportions. The transformation is then obtained as the relationship between the values based on the blood samples and the values given by empirical measurements as measured by the pulse oximeter. The theoretical approach, in turn, is based on a known tissue model, which takes into account the characteristics of the tissue as referred to above, which are ignored in the Lambert-Beer model. A first value is determined for in-vivo Nkl by means of the tissue model and a second value on the basis of the Lambert-Beer model. The tissue parameters of the model are determined so that the known 2-wavelength calibration (so-called R-curve) is reproduced. Then using these tissue parameters and the wavelength dependence of the tissue model, the relation of the in-vivo Nkl and the Lambert-Beer Nkl is extrapolated to other wavelengths in order to obtain the transformations at these new wavelengths. Thus in the theoretical approach no new empirical measurements are made.
In practice the transformation can be a quadratic equation yielding a correction of the order of 20 percent to the measured Nklin-vivo value, for example. As discussed below, the transformation data (i.e. the transformation curves) are preferably stored in numeric form in the pulse oximeter or the sensor. The number of transformation curves stored in the pulse oximeter can vary, depending on the number of wavelengths used, for example. Typically there is a transformation curve for each wavelength pair.
As mentioned above, the accuracy of a pulse oximeter utilizing an average transformation is not necessarily sufficient, especially if analytes which are weak absorbers are to be measured or if two analytes absorb similarly, whereby it is difficult to distinguish the said analytes from each other.
Further, each patient (i.e. subject of the measurement) has a calibration curve of his or her own, which deviates from the average calibration curve calculated on the basis of a high number of patients. This is due to the fact that for each patient the characteristics of the tissue through which light is transmitted deviate from those of an average patient.
This causes one drawback of the current pulse oximeters; they are incapable of taking this human variability into account. Human variability here refers to any and all factors causing patient-specific variation in the calibration curve, including time-dependent changes in the calibration curve of a single patient. As discussed in the above-mentioned U.S. Patent, subject-dependent variation can also be seen as an effect of a third substance, such as a third hemoglobin species in the blood. However, the variation can also be interpreted as a subject-dependent change in the calibration curve of the pulse oximeter.
Without compensation for human variability, the accuracy of current pulse oximeters is about ±2% SpO2. However, in multi-wavelength applications in general, and especially if weak absorbers, such as COHb, are to be measured, the human variability represents a much more serious problem. Therefore, techniques of compensation for these inaccuracies are called for.
It is an objective of the invention to bring about a solution by means of which the effects caused by the tissue of the subject can be taken into account when a pulse oximeter is calibrated. In other words, it is an objective of the present invention to create a pulse oximeter which can take into account the differences caused by an individual subject as compared to the average calibration or transformation curve which the current pulse oximeter relies on.
A further objective of the invention is to bring about a general-purpose solution for the compensation of inaccuracies caused by human variability in pulse oximetry, a solution which is not limited to the particular general calibration method employed in the pulse oximeter, but which can be applied to any pulse oximeter regardless of its current built-in calibration method.